With the advent of the Internet and the subsequent publication of digital data on the web, it is becoming increasingly difficult for the owner of the material to exercise his intellectual property right such as copyright. Technologies are widely available for making accurate copies of digital data. Digital techniques let the original information be recreated in a very accurate manner. Any one can copy the data and claim it as his collection.
In order to uniquely mark the digital data, a technique called watermarking exists in which the digital data is inserted with an invisible watermark. Digital watermarking techniques are used to embed a known piece of digital data within another piece of digital data. The embedded piece of data (watermark) acts as a fingerprint for the owner, allowing the protection of copyright, authentication of the data, and tracing of illegal copies.
This watermark which is normally not known to anybody helps in catching those who copy the data. Any data that is suspected by its owner to have been copied by a third party can examine the suspected data and look for his watermark. If found then he can easily prove his ownership.
One of the older techniques used to embed watermark in the digital data is by Spatial Domain Techniques. Spatial domain techniques work by embedding the data in the spatial domain, in other words, in the image data as it is. The earliest schemes worked by embedding the watermark in the Least Significant Bit (LSB) of the image data. Obviously, such techniques have low reliability. Spatial domain schemes based on different kinds of gray level transformations were proposed. Bruyndoncks et al. proposed a scheme based on pixel region classification. The pixels in an image are classified as pertaining to regions of hard, progressive or noise contrast. Then, the pixels have their gray levels changed following a certain rule that takes into account the region where the pixel is inserted and the value of the bit to be embedded. Kutter proposed a scheme to embed a geometric transformation resistant watermark in the spatial domain by using 2-D amplitude modulation.
Another technique used to embed watermark is Spread Spectrum Technique in which the watermark is introduced in the frequency domain. The most commonly known method for Spread Spectrum Method by Cox et al, described in U.S. Pat. No. 6,208,735, uses spread spectrum communication techniques to embed a bit in the image. Koch et al reported efficient DCT domain watermarking resisting to JPEG compression.
In order to detect watermarks, generally non-blind watermark detection techniques are used. In these techniques, it is required to have the presence of original unmarked data along with the data suspected to be watermarked. In this method, first the original data is transformed to the spatial or any other known domain using Fast Fourier Transformation (FFT) and Discrete Cosine Transformation (DCT) techniques. Then the perceptually significant components are identified and extracted from the marked as well as unmarked data, and then compared to detect the presence of the watermark. Prior art also exists for computing the similarity between the watermark obtained from the suspected watermarked data and the original data.
The disadvantage with the above method is that one has to identify the significant components in both original as well as watermarked data and thereafter compare. This is a complex process, which results in a delay in arriving at the results. Also the accuracy to which the presence of watermark is verified is not very high, because the perceptually significant components might not always contain the watermark.